Will AI take my job?

This article is based on a report lead-authored by Christian Keller, Managing Director and Head of Economics Research at Barclays Investment Bank, in partnership with the IBM Institute for Business Value. They explored how AI could unlock productivity gains in workforces around the world.

When the UK government hosted the ‘AI Safety Summit’ at the tail end of 2023, it was an acknowledgement of the opportunities, but also the challenges, that are emerging from the rapid evolution of Artificial Intelligence (AI). 

The hype surrounding AI is difficult to ignore, thanks to a near-constant stream of opinion pieces, news articles and panel discussions. However, there is one area that is arguably overlooked in current rounds of analysis: the potential for AI to unlock meaningful gains in labour productivity.

Many workers – particularly those in so-called ‘white collar’ jobs – are anxious about the implications of this nascent technology. One common train of thought: if a machine can be trained to work faster and more accurately than I can, and never needs to take a sick day, then why would a company employ a human instead?

Such fears may be misplaced, as we explore in this article.

Pace, potential and policy

Let’s start by considering the US – the world’s biggest economy and a hotbed of technological innovation.

Recent research¹ found that around 80% of the US workforce could have their roles affected by Large Language Models (LLMs) in some way. Large Language Models are a means of summarising large volumes of content and documentation, at pace. 

Such tools are poised to expand rapidly, for two key reasons. First, the technology is available to a very wide audience, on infrastructure that is already in place. Any user can issue basic instructions to a tool such as ChatGPT, the bot developed by OpenAI and launched in November 2022, without having to learn any special programming language. Software providers, for their part, can roll out AI capabilities by bundling them into pre-existing search engines, office suites or even incorporate launchpads into user hardware. 

Second, these tools are not confined to any particular task, function, problem or sector. This makes them usable across different disciplines. Once an LLM is trained on a body of text, for example, it can summarise a legal document as well as it can a medical document or an insurance document. Generative AI systems are not limited to words, either: they can combine text and images with video and audio and even robotic functions.

These two core attributes – accessibility and versatility – suggest that a broad rollout of AI could encounter fewer obstacles than previous advances in technology. By allowing simple or routine tasks to be performed with greater speed and efficiency, it could result in a genuine boost to the production of goods and services, across a variety of industries. As Jerry Kaplan, a Stanford academic, put it several years ago: “automation is blind to the colour of your collar.”

However, unlocking the full potential of AI technology, while simultaneously limiting its negative effects, will require the right policy mix – not only from a regulatory standpoint, but also at the enterprise level. We’re not there yet.

When suitable guardrails are in place, workers who currently fear for their roles may take comfort from the gains in efficiency afforded to them by these technological advancements. 

A much-needed economic catalyst?

In many ways, the evolution of AI could be a welcome shot-in-the-arm for the global economy. 

Ageing workforces in developed countries, and low per-capita output in developing countries, currently act as drags on economic growth. AI could help, in both respects.

How so? Put simply, economic growth is driven by how much labour you put in, and how productive it is. If mature economies can get more out of their pools of labour, raising output-per-hour-worked, they can offset a loss of capacity due to ageing. 

For countries such as Japan, Germany and Italy, for example, workforces are shrinking rapidly enough to require big leaps in labour productivity, just to maintain the kind of GDP growth levels that prevailed before the pandemic. 

But such advances are possible. According to estimates by Barclays Research analysts, most countries would have to attain similar levels of growth in labour productivity that they achieved between 1990 and 1994, to reclaim the average pre-COVID-19 rates of GDP growth in 2033.

And in the emerging world, where skills and education levels tend to be limited, GDP-per-hour-worked is significantly lower. But output could be boosted if workers were to shift into AI-aided services industries. “Service-isation” could take on the role that industrialisation played in the past, when developing nations experienced large gains in productivity and real incomes as workers moved from agriculture into manufacturing. 

Is it worth it?

While the hype around AI is high, early returns on investment (ROI) are low, according to estimates gathered by the IBM Institute for Business Value. Few companies so far have been able to achieve double-digit returns. But successful adoptions of AI could follow a “J-curve” trajectory in ROI – a slow start followed by a rapid rise.

The million-dollar question

All of this bring us nicely to the question raised at the top of the article: Will robots take your job? Probably not, and they might even make it more rewarding. 

The IBM Institute for Business Value has found widespread enthusiasm among business leaders to use AI as a complement to human labour, rather than as a substitute for it. In an August 2023 survey of 3,000 C-suite executives across 20 industries and 28 countries, 87% of respondents saw employees benefitting from, rather than being replaced by, generative AI. 

Ultimately, the benefits for workforces are likely to be driven by a combination of factors, according to the IBM Institute for Business Value, including equipping staff with new skills and fostering innovative workplace cultures that are agile in the face of change. Overlaying all of that is the need for workflow integration, ethical management, and appropriate governance. 

If all this can come together harmoniously, then the value impact of AI could be amplified 17 times, according to the IBM Institute for Business Value. 

For many people monitoring this space, that is something to get excited about. 

Editor’s note: This summary is derived from a whitepaper originally produced by Barclays Research in collaboration with the IBM Institute for Business Value. The information provided does not constitute ‘investment research’ and should not be relied on as such, although it may contain references to views or information published by the Barclays Research department. Investment decisions should not be based upon the information provided.